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What is Velda?

Velda provides a comprehensive development environment that enables developers to run jobs effortlessly in the cloud or cluster, eliminating the need for extra setup. This streamlined access ensures that developers can instantly utilize computational resources, including GPUs, which are crucial for various tasks such as machine learning training, simulations, and batch processing, all while maintaining a user experience similar to local environments and offering extensive customization options. In addition, this solution enhances workflow efficiency, allowing teams to prioritize innovation over the complexities of infrastructure management. By minimizing the hurdles associated with setup and resource allocation, Velda empowers developers to be more productive and creative in their projects.

What is HPE Ezmeral ML OPS?

HPE Ezmeral ML Ops presents a comprehensive set of integrated tools aimed at simplifying machine learning workflows throughout each phase of the ML lifecycle, from initial experimentation to full-scale production, thus promoting swift and flexible operations similar to those seen in DevOps practices. Users can easily create environments tailored to their preferred data science tools, which enables exploration of various enterprise data sources while concurrently experimenting with multiple machine learning and deep learning frameworks to determine the optimal model for their unique business needs. The platform offers self-service, on-demand environments specifically designed for both development and production activities, ensuring flexibility and efficiency. Furthermore, it incorporates high-performance training environments that distinctly separate compute resources from storage, allowing secure access to shared enterprise data, whether located on-premises or in the cloud. In addition, HPE Ezmeral ML Ops facilitates source control through seamless integration with widely used tools like GitHub, which simplifies version management. Users can maintain multiple model versions, each accompanied by metadata, within a model registry, thereby streamlining the organization and retrieval of machine learning assets. This holistic strategy not only improves workflow management but also fosters enhanced collaboration among teams, ultimately driving innovation and efficiency. As a result, organizations can respond more dynamically to shifting market demands and technological advancements.

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Media

Integrations Supported

Amazon EC2
Google Compute Engine
Kubernetes

Integrations Supported

HPE Ezmeral

API Availability

API Availability

Pricing Information

Open source available.
Contact for enterprise pricing.
Free Version

Pricing Information

Pricing not provided

Supported Platforms

SaaS
On-Prem

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
On-Site Training

Training Options

Documentation Hub

Company Facts

Organization Name

Velda

Date Founded

2025

Company Location

United States

Company Website

velda.io

Company Facts

Organization Name

Hewlett Packard Enterprise

Date Founded

2015

Company Location

United States

Company Website

www.hpe.com/us/en/solutions/ezmeral-machine-learning-operations.html

Categories and Features

Application Development

Access Controls/Permissions
Deployment Management
Graphical User Interface
Software Development

Categories and Features

Machine Learning

Not specified

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